code: def _forward(self):
      # Backbone
      body_feats = self.backbone(self.inputs["image"])
      # neck
      neck_feats = self.neck(body_feats)
      # CRL Head
  
      if self.training:
          output = self.heads(neck_feats, self.inputs)
      else:
          output = self.heads(neck_feats)
          output = {"lanes": output}
          # TODO: hard code fix as_lanes=False problem in clrnet_head.py "get_lanes" function for static mode
          if in_dynamic_mode():
              output = self.heads.get_lanes(output["lanes"])
              output = {
                  "lanes": output,
                  "img_path": self.inputs["full_img_path"],
                  "img_name": self.inputs["img_name"],
              }
  
      return output
  
file_path: PaddleDetection/ppdet/modeling/architectures/clrnet.py
imports: from .meta_arch import BaseArch
  from ppdet.core.workspace import register, create
  from paddle import in_dynamic_mode
label_desc: Use image node_id 3 for calling the CLRNet obj's underlying member method code with example usage: obj._forward() and returns: output